Rack Leg Identification for Vehicle Odometry Error Correction
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Solution Overview
Problem
Existing systems for localizing industrial vehicles within warehouse environments using racking systems are inefficient due to inaccuracies in vehicle positioning and lack of effective end-of-aisle protection.
Innovation Solution
A materials handling vehicle equipped with a camera, mast assembly, mast assembly control unit, fork carriage assembly, vehicle position processor, and drive mechanism, which captures images of rack legs to determine coordinates, calculate mast sway offset, and adjust vehicle position accordingly, while also using aisle-specific rack leg spacing data and end-of-aisle limit data to navigate and prevent exceeding end-of-aisle limits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the vehicle uses existing localization systems with racking systems, then the vehicle can navigate within the warehouse, but the vehicle positioning accuracy is insufficient
Solution Approach 1:
The patent replaces traditional mechanical positioning systems with vision-based optical measurement systems. The camera mounted on the vehicle captures images of rack legs, and image processing algorithms determine the vehicle's position and orientation based on the visual features of the racking system, achieving higher positioning accuracy without mechanical contact.
Solution Approach 2:
The patent introduces rack legs as intermediary reference objects between the vehicle and the warehouse environment. By capturing images of these specific rack leg features and using them as reference points for coordinate transformation, the system achieves accurate localization through an intermediary visual reference system rather than direct environmental mapping.
2Measurement precision
If the vehicle operates without mast sway compensation, then the system is simpler, but the vehicle position calibration is inaccurate when forks are elevated
Solution Approach 1:
The patent performs preliminary calibration by capturing images at multiple known mast heights (forks down, forks up, and intermediate positions) before actual operation. This preliminary data collection establishes the relationship between mast position and vehicle coordinate system, enabling accurate position calibration during subsequent operations without requiring complex real-time compensation mechanisms.
Solution Approach 2:
The patent makes the vehicle coordinate system dynamic by adapting it to different mast positions. The system captures images at various mast heights and adjusts the coordinate transformation parameters accordingly, allowing the localization system to remain accurate whether the forks are down or elevated, rather than using a fixed coordinate system.
3Reliability
If the vehicle lacks end-of-aisle protection, then the device is simpler, but the vehicle may overrun the end of aisles causing safety issues
Solution Approach 1:
The patent implements feedback-based end-of-aisle protection by continuously monitoring the vehicle's position relative to aisle boundaries using rack leg identification. The system provides feedback signals to the vehicle controller to alert the operator or automatically adjust navigation when approaching aisle ends, preventing overruns through continuous position feedback rather than physical barriers.
Solution Approach 2:
The patent applies preliminary anti-action by detecting approaching end-of-aisle conditions before the vehicle actually reaches the boundary. The system uses rack leg spacing and position data to predict when the vehicle will reach the aisle end and takes preventive action by alerting the operator or adjusting the navigation path in advance, preventing the harmful overrun condition before it occurs.
Data Source
AI summary
A materials handling vehicle includes a camera, odometry module, processor, and drive mechanism. The camera captures images of an identifier for a racking system aisle and a rack leg portion in the aisle. The processor uses the identifier to generate information indicative of an initial rack leg position and rack leg spacing in the aisle, generate an initial vehicle position using the initial rack leg position, generate a vehicle odometry-based position using odometry data and the initial vehicle position, detect a subsequent rack leg using a captured image, correlate the detected subsequent rack leg with an expected vehicle position using rack leg spacing, generate an odometry error signal based on a difference between the positions, and update the vehicle odometry-based position using the odometry error signal and/or generated mast sway compensation to use for end of aisle protection and/or in/out of aisle localization.